Full papers
4+N or 8+N page formats (4 or 8 pages of main content with unlimited additional pages for references and appendices); accepted papers will be invited for poster presentations, with highest-rated papers given spotlight presentations.
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RSS SemRob 2026
3rd Workshop on Semantic Reasoning and Goal Understanding in Robotics (RSS 2026)
RSS SemRob 2026 is a workshop held in conjunction with the Robotics Science and Systems Conference (RSS 2026) in Sydney, Australia, focused on semantic reasoning and goal understanding in robotics. It brings together researchers to explore how semantic structures can enhance data efficiency, generalization, safety, and interpretability in robot learning through interdisciplinary approaches in neuro-symbolic AI, vision-language-action models, and embodied reasoning.
Key deadlines
Verified September 9, 2026Full paper
June 19, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
June 19, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Research areas in scope
01
Targeted Topics
Semantic representations for generalizable robot learning, including object-centric representations, affordances, skill abstractions, geometric task-space primitives, pre-/post-conditions, constraints, and action tokenizationVision-language-action models, robot foundation models, and generalist policies that connect semantic understanding with embodied controlHybrid neural-symbolic architectures that combine learned representations with structured scene representations, knowledge graphs, scene graphs, task graphs, or procedural reasoningWorld models and dynamics models for robot learning, including predictive simulation, synthetic data generation, policy training, planning, evaluation, and sim-to-real transferCross-embodiment robot learning, including shared action spaces, embodiment-invariant task representations, morphology-aware policies, and transfer across robot platformsTest-time adaptation, policy steering, online policy guidance, and failure recovery for robots operating in uncertain or changing environmentsHuman-in-the-loop robot learning, including online policy supervision, preference feedback, corrective demonstrations, interactive teaching, and behavior repairSemantic memory mechanisms for storing, retrieving, and reusing experience across tasks, environments, and interaction historiesMetacognitive and self-reflective mechanisms for robot learning, including uncertainty estimation, calibration, self-critique, chain-of-thought-style reasoning, agentic reasoning structures, and confidence-aware controlSafety-aware semantic reasoning for learned robot policies, including constraint satisfaction, risk-aware decision-making, verification, monitoring, and intervention mechanismsData-efficient and scalable robot learning methods that exploit semantic structure, task decomposition, compositionality, or foundation-model priorsBenchmarks, datasets, and evaluation protocols for semantic generalization, long-horizon behavior, cross-task transfer, and real-world robustness
Policies worth checking twice
- Submission process is double-blind, following RSS 2026 paper submission policy for Science/Systems papers
- Dual submission is welcome: new, under-review, or recently published work is accepted
- Accepted papers are non-archival and will not be included in any official proceedings
- Papers must be submitted as PDF files via OpenReview using official RSS 2026 LaTeX or Word templates
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026